In recent years the technique of hydraulic fracturing has become widely used for recovery of hydrocarbon reserves, and in particular, of natural gas from shale formations deep underground. Monitoring the progress of the fracturing is important for technical and environmental reasons. One method of monitoring the fracturing process in close to real time uses the energy released by the fracturing of the geologic formation under very high pressure. This energy can be detected as seismic waves, which are recorded as digital data. Such seismic waves possess relatively low energy when compared to those generated by earthquakes or conventional seismic surveying with impulsive or vibratory sources, and as a result, this branch of geophysics is therefore referred to as “microseismic”.
Because the seismic energy released by microseismic events is so low, any reduction in noise levels provides advantages in data processing and identification of microseismic events. Various techniques are available for filtering noise, but many rely either on being able to identify the noise from a characteristic pattern exhibited at different sensor locations at different times, or on noise being cancelled out when data from multiple sensor locations are stacked. Some sensor geometry arrays have been used to reduce noise levels, but in many such approaches, such as star or radial arrays, it is assumed that noise originates at one point, usually in the well in which the fracturing operation is taking place. This is not always the case, however, as noise may originate from many sources. When a second or subsequent well is drilled, a new array has to be laid out that is centered on the new well.
What is required is a generalized and flexible sensor array geometry, with the orientation of the sensor lines and the sensor spacing designed to provide the information required to discriminate against various forms of noise originating at multiple locations, and to enhance weak microseismic signals.